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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 11–20 of 347 papers

TitleStatusHype
Convolutional Neural Operators for robust and accurate learning of PDEsCode2
Neural Operator: Learning Maps Between Function SpacesCode2
Mesh-Informed Neural Operator : A Transformer Generative ApproachCode1
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator LearningCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Improve Representation for Imbalanced Regression through Geometric ConstraintsCode1
RIGNO: A Graph-based framework for robust and accurate operator learning for PDEs on arbitrary domainsCode1
Point-DeepONet: A Deep Operator Network Integrating PointNet for Nonlinear Analysis of Non-Parametric 3D Geometries and Load ConditionsCode1
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problemsCode1
VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics PredictionCode1
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